Efficient cooling of high temperature synthesis gas produced in underground coal gasification systems is essential for improving thermal efficiency and ensuring safe operation of downstream processing units. Membrane helical coil heat exchangers have demonstrated significant advantages in heat transfer enhancement due to the presence of curvature induced secondary flows. However, optimizing the geometric and operating parameters of such systems remains a complex engineering problem involving multiple conflicting objectives, such as maximizing heat transfer while minimizing pressure drop.

This study presents a multi objective optimization approach for membrane helical coil heat exchangers used for high pressure syngas cooling. Computational Fluid Dynamics (CFD) simulations were first conducted to evaluate the thermo-hydraulic performance of the heat exchanger under various geometric and operating conditions. The obtained results were then used to develop surrogate models that relate design parameters to system performance. A Genetic Algorithm (GA) based optimization framework was implemented to simultaneously maximize the Nusselt number and minimize the friction factor.

The optimization process considered key design variables including coil diameter, tube diameter, pitch ratio, and Reynolds number. The Pareto optimal solutions obtained from the genetic algorithm reveal the trade-off between enhanced heat transfer and pressure loss in the helical coil configuration. The optimal design identified in this study achieved a thermo-hydraulic performance factor of approximately 1.31, representing a significant improvement over conventional designs.

The findings demonstrate that multi objective optimization techniques can effectively guide the design of advanced heat exchangers for high temperature gas cooling applications. The proposed optimization framework provides a systematic methodology for improving thermal performance and energy efficiency in underground coal gasification systems and other high-temperature industrial processes.